SBIR Phase II: Mnemonic Optimization of Music and Songs

Award ID: 1927160

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project further investigates music-based techniques that can result in effective and efficient learning and instruction. Music as a bedrock of culture can transcend entertainment and enhance learning. Music directly activates neural systems that support memory, attention, motivation, and emotion. Accordingly, music is a powerful medium that not only heightens learner engagement but also facilitates retention of information. While music has long been recognized for its mnemonic properties and is widely used as a memory aid in the context of early childhood learning (e.g., the ABC song), music-based educational products for the broader K-12 market are less pervasive. This project focuses on the optimization of musical structures to support effective and engaging mathematics instruction. The goal of this project is to offer music as a credible pedagogical tool. Specifically, this project offers music as a learning medium that can be used beyond rote memorization and instead teach mathematical skills, processes, and procedures in an engaging manner that makes math accessible to all learners. Mathematical fluency is a critical skill in a society that continues to become more technological; it also creates broader career opportunities for students and undergirds the U.S.'s national competitiveness. The proposed research features two innovations: 1) optimization of learning-based musical forms based on distinct mathematical information types; and 2) creation of a non-linear, dynamic platform to deliver the content. Using computational musicology techniques as well as experimental studies, the first innovation involves creation of mathematically accurate music videos based on unique creative and structural parameters that are determined by the type of mathematical information being taught. The second innovation focuses on delivery of the music-based content and involves significant technical and creative investigation to produce a dynamic, non-linear mechanism for presenting the material in a manner that still feels continuous and compelling to the student. Together, both innovations underlie a synergistic learning solution designed for premium learner engagement and to support self-paced, adaptive learning. This project will result in high quality, digital math instruction that is accessible to all learners through use of effective, engaging, and relevant instructional methods. The desired outcomes are eliminating proficiency gaps in math education and achieving equity in students' educational success. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Rajesh Mehta